Automated selection of functions to reduce storage capacity based on performance requirements

ABSTRACT

A plurality of functions to configure a unit of a storage volume is maintained, wherein each of the plurality of functions, in response to being applied to the unit of the storage volume, configures the unit of the storage volume differently. Statistics are computed on growth rate of data and access characteristics of the data stored in the unit of the storage volume. A determination is made as to which of the plurality of functions to apply to the unit of the storage volume, based on the computed statistics.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.13/469,002, filed May 10, 2012, wherein U.S. patent application Ser. No.13/469,002 is a continuation of U.S. patent application Ser. No.13/247,283 filed Sep. 28, 2011, wherein U.S. patent application Ser.Nos. 13/469,002 and 13/247,283 are incorporated herein by reference intheir entirety.

BACKGROUND

1. Field

The disclosure relates to a method, system, and computer program productfor the automated selection of functions to reduce storage capacitybased on performance requirements.

2. Background

Many features that are deployed in storage systems aim to reducebusiness costs. For example, data reduction or free space reclamationmay be used to reduce the need for storage capacity. In certainsituations, such features may be deployed via thin provisioning in whichfree space is reclaimed, via deduplication in which multiple referencesmay be maintained to a single data stream, or via data compression inwhich data is reduced by applying either lossy or lossless compressionmechanisms.

In thin provisioning a storage volume may be defined but storage spacemay be allocated for the storage volume only when write operations areperformed to the storage volume. In data duplication only a single copyof a set of duplicate data may be maintained and pointers may bemaintained such that the locations at which the original duplicate datawas stored can be determined In data compression lossy compression maycause a greater reduction in storage requirements in comparison tolossless compression. It may be noted that storage space requirementsmay be reduced via thin provisioning, via data duplication, and via datacompression. In contrast to thin provisioning, data duplication, or datacompression that reduce storage space requirements, a fully allocatedvolume may not have any thin provisioning, data duplication, or datacompression, and may not reduce storage space requirements.

SUMMARY OF THE PREFERRED EMBODIMENTS

Provided are a method, a system, and a computer program product, whereina plurality of functions to configure a unit of a storage volume ismaintained, wherein each of the plurality of functions, in response tobeing applied to the unit of the storage volume, configures the unit ofthe storage volume differently. Statistics are computed on growth rateof data and access characteristics of the data stored in the unit of thestorage volume. A determination is made as to which of the plurality offunctions to apply to the unit of the storage volume, based on thecomputed statistics.

In certain embodiments, the plurality of functions include thinprovisioning, wherein the computed statistics include determining a rateat which write operations are performed on the unit of the storagevolume and an available amount of unused space on the unit of thestorage volume. Thin provisioning is applied to the unit of the storagevolume, in response to determining that the rate at which writeoperations are performed on the unit of the storage volume does notexceed a predetermined rate of write operations and the available amountof unused space on the unit of the storage volume exceeds apredetermined threshold.

In certain additional embodiments, the plurality of functions includesdata deduplication, wherein the computed statistics include determininghow much duplicative data is present on the unit of the storage volume.Data deduplication is applied to the unit of the storage volume, inresponse to determining that duplicative data present on the unit of thestorage volume exceeds a predetermined threshold and the access timerequirement for the unit of the storage volume is greater than apredetermined access time rate.

In further embodiments, the plurality of functions includes fullallocation. Full allocation is applied to the unit of the storagevolume, in response to determining that access time requirement for theunit of the storage volume is less than a predetermined threshold amountof time.

In yet further embodiments, the plurality of functions include datacompression, wherein the computed statistics include determining howmuch the data stored on the unit of the storage volume is capable ofbeing compressed. The data stored on the unit of the storage volume iscompressed, in response to determining that access time requirement forthe data will be met subsequent to the compressing of the data stored inthe unit of the storage volume.

In additional embodiments, the plurality of functions includes fullallocation, thin provisioning, data compression, and data deduplicationin a decreasing order of performance in terms of performing operationson the unit of the storage volume, and in an increasing order ofefficiency in terms of storage requirements in the unit of the storagevolume.

In yet additional embodiments, the unit of the storage volume is anextent that comprises a predetermined number of kilobytes.

In further embodiments, a selected unit of a selected storage volume isupgraded or downgraded in terms of access time or storage efficiency byapplying a different function to data stored in the selected unit of theselected storage volume.

BRIEF DESCRIPTION OF THE DRAWINGS

Referring now to the drawings in which like reference numbers representcorresponding parts throughout:

FIG. 1 illustrates a block diagram of a computing environment thatincludes a storage controller coupled to a plurality of storage devices,in accordance with certain embodiments;

FIG. 2 illustrates a block diagram that shows how a statistics collectorapplication implemented in the storage controller collects statistics ondata stored in units of storage volumes corresponding to the pluralityof storage devices, in accordance with certain embodiments;

FIG. 3 illustrates a block diagram that shows how a functiondetermination application implemented in the storage controllerdetermines which function to apply on data stored in units of storagevolumes corresponding to the plurality of storage devices, in accordancewith certain embodiments;

FIG. 4 illustrates a block diagram that shows how a set of functions maybe placed in a relationship with respect to reduction in storage spaceand reduction in access time, in accordance with certain embodiments;

FIG. 5 illustrates a flowchart that shows operations performed by thestorage controller, in accordance with certain embodiments;

FIG. 6 illustrates an implementation of a node in a network computingembodiment;

FIG. 7 illustrates an embodiment of a cloud computing environment;

FIG. 8 illustrates an embodiment of abstraction model layers of a cloudcomputing environment; and

FIG. 9 illustrates a block diagram of a computational system that showscertain elements that may be included in the storage controller of FIG.1, in accordance with certain embodiments.

DETAILED DESCRIPTION

In the following description, reference is made to the accompanyingdrawings which form a part hereof and which illustrate severalembodiments. It is understood that other embodiments may be utilized andstructural and operational changes may be made.

Application of Features to Reduce Storage Capacity Needs

Various systems may provide one of more types of features for reductionof storage capacity needs, but it may be up to the user to decide whichof the features are applicable to the particular data volumes theyintend to provision. Additionally, the features to apply may be decidedat the time of provisioning a volume, and to change the application ofone feature to another may need user intervention and some detailedanalysis of the benefits that each feature may or may not provide.

Certain embodiments allow a dynamic analysis of the behavior of a givenvolume and an automatic determination as to which of the availablefeatures best suits the data creation and subsequent accesscharacteristics of the given volume. Certain embodiments allow themigration of a volume to provide the best feature based on the dynamicanalysis of the creation and access characteristics. Such embodimentsallow an automated determination as to which features are best suited tobe applied to the data stored on a storage volume. As a result, endusers do not have to manually determine whether a given feature isapplicable for a selected volume.

In certain embodiments statistics are maintained (on a per volume basis)on data growth rates and access characteristics for the data. Themaintained statistics allow the system to determine which function touse on the data based on some predefined templates that define usagecharacteristics of each function (e.g., thin provisioning,deduplication, compression, etc.).

In certain embodiments, a determination is made as to whether a storagevolume can be “down featured” or downgraded. Down featured meanschanging the function that is applied to a storage volume such thatthere is a reduction is access speed but an increase in storagecapacity. For example, a new volume may always be provisioned as a fullyallocated volume that does not use thin provisioning, deduplication,compression, etc. The system runs for a period of time and accumulatessome statistics that provide the growth and access patterns. The systemcan then decide that if on the continuum of features, the data on thisvolume is well suited to compression, and if the compression throughputrates can meet the access characteristics, then the volume can be “downfeatured” from fully allocated to compressed.

Exemplary Embodiments

FIG. 1 illustrates a block diagram of a computing environment 100 thatincludes a storage controller 102 coupled to a plurality of storagedevices 104 a . . . 104 n, in accordance with certain embodiments. Incertain embodiments the computing environment 100 may be part of a cloudcomputing environment. The storage controller 102 may comprise anysuitable computational device including those presently known in theart, such as, a personal computer, a workstation, a server, a mainframe,a hand held computer, a palm top computer, a telephony device, a networkappliance, a blade computer, a server, etc. The plurality of storagedevices 104 a . . . 104 n may include any suitable storage devices, suchas, hard disks, solid state disks, optical disks, tapes, etc.

The storage controller 102 controls the plurality of storage devices 104a . . . 104 n and creates a plurality storage volumes 106 a . . . 106 mthat logically represent data stored in the plurality of storage devices104 a . . . 104 n. Each storage volume may be comprised of a pluralityof units, such as extents, blocks, etc. For example, in FIG. 1 storagevolume 106 a is shown as being comprised of a plurality of extents 108 a. . . 108 p.

The storage controller 102 includes a statistics generator application110, a function determination application 112, a deduplicationapplication 114, a compression application 116, a thin provisioningapplication 118, and a full allocation application 120. The storagecontroller 102 also maintains a plurality of predetermined thresholds122 and other information related to the performance and characteristicsof the deduplication application 114, the compression application 116,the thin provisioning application 118, and the full allocationapplication 120.

The statistics collector application 110 generates statistics comprisingmetadata related to the data stored in the plurality of storage volumes106 a . . . 106 m. The function determination application 112 uses thestatistics generated by the statistics collector application 110 andbased on computations made by using the thresholds 122 determines whichof the deduplication application 114, the compression application 116,the thin provisioning application 118, or the full allocationapplication 120 to apply to data stored in units of the storage volumes106 a . . . 106 m.

FIG. 2 illustrates a block diagram 200 that shows how the statisticscollector application 110 implemented in the storage controller 102collects statistics on data stored in units of storage volumes 106 a . .. 106 m corresponding to the plurality of storage devices 104 a . . .104 n, in accordance with certain embodiments.

In certain embodiments the statistics collector application 110generates statistics, per storage volume or per unit (e.g., extent). Thecollected statistics may also be referred to as metadata. The collectedstatistics may relate to data growth rate 202 and access characteristics204. Other statistics may also be generated.

Data growth rate 202 may be a measure of how fast the used capacity on astorage volume or unit is growing. For example, the data growth rate ofa selected unit may be estimated to be 2 kilobytes per day based onhistorical data growth patterns in the selected unit, wherein the datagrowth may be caused at least by write operations.

Access characteristics 204 may include a measure of the speed of dataaccess for input/output (I/O) operations such as read, write, append,etc. The performance 206, peak throughput rates (in megabytes persecond, Input Output operations per second, etc.) 208, response time210, etc., may be measured. In certain embodiments, the accesscharacteristics may also determine the locality of access.

FIG. 3 illustrates a block diagram 300 that shows how the functiondetermination application 112 implemented in the storage controller 102determines which function to apply on data stored in units of storagevolumes 106 a . . . 106 m corresponding to the plurality of storagedevices 104 a . . . 104 n, in accordance with certain embodiments.

The function determination application 112 analyzes the statistics 302collected by the statistics collector application 110 and uses thepredetermined thresholds 122 to determine whether to deduplicate 304,compress 306, thinly provision 308, or fully allocate 310 units orstorage volumes. If deduplication 304 is desired then the deduplicationapplication 114 is applied to data stored in units of the storagevolumes 106 a . . . 106 m. If compression 306 is desired than thecompression application 116 is applied to data stored in units of thestorage volumes 106 a . . . 106 m. If thin provisioning 308 is desiredthen the thin provisioning application 118 is applied to data stored inunits of the storage volumes 106 a . . . 106 m. If full allocation 310is desired then the full allocation application 120 is applied to datastored in units of the storage volumes 106 a . . . 106 m.

FIG. 4 illustrates a block diagram 400 that shows how a set of functionsmay be placed in a relationship with respect to reduction in storagespace and reduction in access time, in accordance with certainembodiments.

In certain embodiments, a determination may be performed for a volume orfor a unit of a volume on the compressibility, deduplicability, thinprovisioning capability of the volume or the unit. With this data, ananalysis can be made that is then cross-referenced with knownlimitations of each function.

In an exemplary embodiment, the function determination application 112may use the data growth statistics to determine that the source volumeis only 20% utilized and growing at only 1% per month, In such asituation, it may be appropriate to free up the 80% unallocated spacefor use by other volumes and the thin provisioning application 118 maybe applied because not too many write operations that grow the volumeare taking place.

The net result is that over time, the system may automatically migratethe volumes to use the correct feature for the correct volume, withoutany intervention from the end user. Certain embodiments decouple the enduser from the complexity of the storage system and its availablefeatures. It is also possible to change the application of functionsbased on change in access statistics.

Deduplication may have limited throughput capability because many smallblock reads may be needed to rebuild a data block from the deduplicateddata. On writes, deduplication may have to build hash data, and look upany duplicates and this may result in additional processor usage As aresult, deduplication may have a certain MB/s, I/O operations/s andresponse time characteristics.

Compression is mainly limited both on reads and writes by thecompression algorithm and may be somewhat faster in terms of access timethan deduplication.

Thin Provisioning has most of its impact on writes, and in particularwrites to new areas of disk, and so may provide faster access times thaneither compression or deduplication.

This gives a continuum of features as shown in FIG. 4 from fullyallocated 402 to thinly provisioned 404 to compressed 406 todeduplicated 408, from highest performing to lowest performing as shownvia reference numeral 410 in FIG. 4. However, the greatest storageefficiency (shown via reference numeral 412) in obtained in situationswhere the performance is the lowest.

This background information on the limitations of each feature can beused to determine if the volume being analyzed may be “down featured”.Based on the current access characteristics indicated via throughput, ifthe access characteristics can be contained, the system may run a sample“down feature” process for a small subset of the volume data. Forexample, if compression is chosen, then a scratch volume may betemporarily created, and the compression application 116 may run on thesubset of volume data to determine if the overheads of compression areworth in terms of disk usage savings. The same applies fordeduplication. Based on such sample runs a decision may be made as towhether to achieve greater storage efficiency at the cost of greateraccess time.

It should be noted that, in certain embodiments the plurality ofexemplary functions, such as full allocation 402, thin provisioning 404,compression 406, and deduplication may be performed in a different orderthan the order shown in FIG. 4. Also, in certain embodiments a pluralityof exemplary functions may be active on the same extent, block, etc. Forexample, in certain embodiments, both deduplication and compressionfunctions may be active on the same extent. The functions 402, 404, 406,408 shown in FIG. 4 are for purposes of illustration, and in otherembodiments additional functions that are not shown in FIG. 4 may beapplied.

FIG. 5 illustrates a flowchart 500 that shows operations performed bythe storage controller 102, in accordance with certain embodiments. Theoperations shown in FIG. 5 may be performed by applications executingwithin the storage controller 102.

Control starts at block 502 in which a plurality of functions toconfigure a unit of a storage volume is maintained, wherein each of theplurality of functions, in response to being applied to the unit of thestorage volume, configures the unit of the storage volume differently.

Control proceeds to block 504 in which statistics are computed on growthrate of data and access characteristics of the data stored in the unitof the storage volume. A determination is made (at block 506) as towhich of the plurality of functions to apply to the unit of the storagevolume, based on the computed statistics.

In additional embodiments, the plurality of functions includes fullallocation 120, thin provisioning 118, data compression 116, and datadeduplication 114 in decreasing order of performance 410 in terms ofperforming operations on the unit of the storage volume, and in anincreasing order of efficiency 412 in terms of storage requirements inthe unit of the storage volume. Volumes may be upgraded or downgraded interms of access times and storage efficiency by applying differentfunctions to the data stored in the volumes.

Certain embodiments may examine “chunks”, i.e., units, of each volumeand determine based on performance, if that chunk should be moved up ordown a tier. For example, a very high performing chunk may be stored ona solid state disk (SSD), a low performing chunk on serially coupleddevices, etc. In certain embodiments, it may be determined that a chunkX is very infrequently accessed and so that chunk X may be compressed,while chunk Y is very frequently accessed, and chunk Y may remain as afully allocated chunk. This may mean that a volume may be using all,some, or none of the advanced features for reduction of storage, but theembodiments take the granularity from a volume level to a chunk level.

Therefore FIGS. 1-5 illustrate certain embodiments in which adetermination is made based on usage statistics of access time andstorage requirements which of a plurality of functions to reduce datastorage requirements is to be applied to data stored in storage volumes.

Cloud Computing Embodiments

The computing environment 100 of FIG. 1 may be part of a cloud computingmodel of service delivery for enabling convenient, on-demand networkaccess to a shared pool of configurable computing resources (e.g.networks, network bandwidth, servers, processing, memory, storage,applications, virtual machines, and services) that can be rapidlyprovisioned and released with minimal management effort or interactionwith a provider of the service. The cloud computing implementation isdescribed with respect to FIGS. 6-8. This cloud model may include atleast five characteristics, at least three service models, and at leastfour deployment models.

The at least five characteristics of the cloud model are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick source platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

The at least three service models are as follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various source devices through athin source interface such as a web browser (e.g., web-based e-mail).The consumer does not manage or control the underlying cloudinfrastructure including network, servers, operating systems, storage,or even individual application capabilities, with the possible exceptionof limited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

The at least four deployment models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

FIG. 6 illustrates an embodiment of a cloud computing node 600 which maycomprise an implementation of the storage controller 102 and storagedevice 104 a . . . 104 n components, where the components may beimplemented in one or more of the nodes 600. Cloud computing node 600 isonly one example of a suitable cloud computing node and is not intendedto suggest any limitation as to the scope of use or functionality ofembodiments of the invention described herein. Regardless, cloudcomputing node 600 is capable of being implemented and/or performing anyof the functionality set forth hereinabove.

In cloud computing node 600 there is a computer system/server 602, whichis operational with numerous other general purpose or special purposecomputing system environments or configurations. Examples of well-knowncomputing systems, environments, and/or configurations that may besuitable for use with computer system/server 602 include, but are notlimited to, personal computer systems, server computer systems, thinsources, thick sources, handheld or laptop devices, multiprocessorsystems, microprocessor-based systems, set top boxes, programmableconsumer electronics, network PCs, minicomputer systems, mainframecomputer systems, and distributed cloud computing environments thatinclude any of the above systems or devices, and the like.

Computer system/server 602 may be described in the general context ofcomputer system executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 602 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage devices.

As shown in FIG. 6, computer system/server 602 in cloud computing node600 is shown in the form of a general-purpose computing device. Thecomponents of computer system/server 602 may include, but are notlimited to, one or more processors or processing units 604, a systemmemory 606, and a bus 608 that couples various system componentsincluding system memory 606 to processor 604.

Bus 608 represents one or more of any of several types of busstructures, including a memory bus or memory controller, a peripheralbus, an accelerated graphics port, and a processor or local bus usingany of a variety of bus architectures. By way of example, and notlimitation, such architectures include Industry Standard Architecture(ISA) bus, Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA)bus, Video Electronics Standards Association (VESA) local bus, andPeripheral Component Interconnects (PCI) bus.

Computer system/server 602 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 602, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 606 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 610 and/or cachememory 612. Computer system/server 602 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 613 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 608 by one or more datamedia interfaces. As will be further depicted and described below,memory 606 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 614, having a set (at least one) of program modules 616,may be stored in memory 606 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 616 generally carry out the functionsand/or methodologies of embodiments of the invention as describedherein.

Computer system/server 602 may also communicate with one or moreexternal devices 618 such as a keyboard, a pointing device, a display620, etc.; one or more devices that enable a user to interact withcomputer system/server 602; and/or any devices (e.g., network card,modem, etc.) that enable computer system/server 602 to communicate withone or more other computing devices. Such communication can occur viaInput/Output (I/O) interfaces 622. Still yet, computer system/server 602can communicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 624. As depicted, network adapter 624communicates with the other components of computer system/server 602 viabus 608. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 602. Examples, include, but are not limited to: microcode,device drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

Referring now to FIG. 7, illustrative cloud computing environment 750 isdepicted. As shown, cloud computing environment 750 comprises one ormore cloud computing nodes 600 with which local computing devices usedby cloud consumers, such as, for example, personal digital assistant(PDA) or cellular telephone 754A, desktop computer 754B, laptop computer754C, and/or automobile computer system 754N may communicate. Nodes 600may communicate with one another. They may be grouped (not shown)physically or virtually, in one or more networks, such as Private,Community, Public, or Hybrid clouds as described hereinabove, or acombination thereof. This allows cloud computing environment 750 tooffer infrastructure, platforms and/or software as services for which acloud consumer does not need to maintain resources on a local computingdevice. It is understood that the types of computing devices 754A-Nshown in FIG. 7 are intended to be illustrative only and that computingnodes 600 and cloud computing environment 750 can communicate with anytype of computerized device over any type of network and/or networkaddressable connection (e.g., using a web browser).

Further, FIG. 7 shows a single cloud. However, certain cloud embodimentsmay provide a deployment model including a separate “Backup” or “DataProtection” cloud, in addition to the cloud having thecustomer/production data. Providing a separate and distinct additionalcloud as the data protection cloud in order to separate whatever primarycloud model (provide, community, hybrid, etc) from the data protectioncloud prevents a single point of failure and provides a greater degreeof protection of the customer data in the separate backup cloud.

Referring now to FIG. 8, a set of functional abstraction layers providedby cloud computing environment 750 (FIG. 7) is shown. It should beunderstood in advance that the components, layers, and functions shownin FIG. 8 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 860 includes hardware and softwarecomponents. Examples of hardware components include mainframes, in oneexample IBM® zSeries® systems; RISC (Reduced Instruction Set Computer)architecture based servers, in one example IBM pSeries® systems; IBMxSeries® systems; IBM BladeCenter® systems; storage devices; networksand networking components. Examples of software components includenetwork application server software, in one example IBM WebSphere®application server software; and database software, in one example IBMDB2® database software. (IBM, zSeries, pSeries, xSeries, BladeCenter,WebSphere, and DB2 are trademarks of International Business MachinesCorporation registered in many jurisdictions worldwide).

Virtualization layer 862 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers;virtual storage; virtual networks, including virtual private networks;virtual applications and operating systems; and virtual sources.

In one example, management layer 864 may provide the functions describedbelow. Resource provisioning provides dynamic procurement of computingresources and other resources that are utilized to perform tasks withinthe cloud computing environment. Metering and Pricing provide costtracking as resources are utilized within the cloud computingenvironment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal provides access to the cloud computing environment forconsumers and system administrators. Service level management providescloud computing resource allocation and management such that requiredservice levels are met. Service Level Agreement (SLA) planning andfulfillment provide pre-arrangement for, and procurement of, cloudcomputing resources for which a future requirement is anticipated inaccordance with an SLA.

Workloads layer 866 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation; software development and lifecycle management; virtualclassroom education delivery; data analytics processing; transactionprocessing; and the statistics collection, function determination,deduplication, compression, thin provisioning, and full allocationservices, such as those described with respect to FIGS. 1-5, above.

Additional Embodiment Details

The described operations may be implemented as a method, apparatus orcomputer program product using standard programming and/or engineeringtechniques to produce software, firmware, hardware, or any combinationthereof. Accordingly, aspects of the embodiments may take the form of anentirely hardware embodiment, an entirely software embodiment (includingfirmware, resident software, micro-code, etc.) or an embodimentcombining software and hardware aspects that may all generally bereferred to herein as a “circuit,” “module” or “system.” Furthermore,aspects of the embodiments may take the form of a computer programproduct embodied in one or more computer readable medium(s) havingcomputer readable program code embodied there.

Any combination of one or more computer readable medium(s) may beutilized. The computer readable medium may be a computer readable signalmedium or a computer readable storage medium. A computer readablestorage medium may be, for example, but not limited to, an electronic,magnetic, optical, electromagnetic, infrared, or semiconductor system,apparatus, or device, or any suitable combination of the foregoing. Morespecific examples (a non-exhaustive list) of the computer readablestorage medium would include the following: an electrical connectionhaving one or more wires, a portable computer diskette, a hard disk, arandom access memory (RAM), a read-only memory (ROM), an erasableprogrammable read-only memory (EPROM or Flash memory), an optical fiber,a portable compact disc read-only memory (CD-ROM), an optical storagedevice, a magnetic storage device, or any suitable combination of theforegoing. In the context of this document, a computer readable storagemedium may be any tangible medium that can contain, or store a programfor use by or in connection with an instruction execution system,apparatus, or device.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including, but not limited to,electro-magnetic, optical, or any suitable combination thereof. Acomputer readable signal medium may be any computer readable medium thatis not a computer readable storage medium and that can communicate,propagate, or transport a program for use by or in connection with aninstruction execution system, apparatus, or device.

Program code embodied on a computer readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber cable, RF, etc., or any suitable combination ofthe foregoing.

Computer program code for carrying out operations for aspects of thepresent invention may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as Java*, Smalltalk, C++ or the like and conventional proceduralprogramming languages, such as the “C” programming language or similarprogramming languages. The program code may execute entirely on theuser's computer, partly on the user's computer, as a stand-alonesoftware package, partly on the user's computer and partly on a remotecomputer or entirely on the remote computer or server. In the latterscenario, the remote computer may be connected to the user's computerthrough any type of network, including a local area network (LAN) or awide area network (WAN), or the connection may be made to an externalcomputer (for example, through the Internet using an Internet ServiceProvider). * Java is a trademark or registered trademark of Oracleand/or its affiliates.

* IBM, zSeries, pSeries, xSeries; BladeCenter, WebSphere, DB2 aretrademarks or registered trademarks of IBM corporation.

Aspects of the present invention are described below with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

These computer program instructions may also be stored in a computerreadable medium that can direct a computer, other programmable dataprocessing apparatus, or other devices to function in a particularmanner, such that the instructions stored in the computer readablemedium produce an article of manufacture including instructions whichimplement the function/act specified in the flowchart and/or blockdiagram block or blocks.

The computer program instructions may also be loaded onto a computer,other programmable data processing apparatus, or other devices to causea series of operational steps to be performed on the computer, otherprogrammable apparatus or other devices to produce a computerimplemented process such that the instructions which execute on thecomputer or other programmable apparatus provide processes forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks.

FIG. 9 illustrates a block diagram that shows certain elements that maybe included in the storage controller 102, in accordance with certainembodiments. The system 900 may comprise the storage controller 102 andmay include a circuitry 902 that may in certain embodiments include atleast a processor 904. The system 900 may also include a memory 906(e.g., a volatile memory device), and storage 908. The storage 908 mayinclude a non-volatile memory device (e.g., EEPROM, ROM, PROM, RAM,DRAM, SRAM, flash, firmware, programmable logic, etc.), magnetic diskdrive, optical disk drive, tape drive, etc. The storage 908 may comprisean internal storage device, an attached storage device and/or a networkaccessible storage device. The system 900 may include a program logic910 including code 912 that may be loaded into the memory 906 andexecuted by the processor 904 or circuitry 902. In certain embodiments,the program logic 910 including code 912 may be stored in the storage908. In certain other embodiments, the program logic 910 may beimplemented in the circuitry 902. Therefore, while FIG. 9 shows theprogram logic 910 separately from the other elements, the program logic910 may be implemented in the memory 906 and/or the circuitry 902.

Certain embodiments may be directed to a method for deploying computinginstruction by a person or automated processing integratingcomputer-readable code into a computing system, wherein the code incombination with the computing system is enabled to perform theoperations of the described embodiments.

The terms “an embodiment”, “embodiment”, “embodiments”, “theembodiment”, “the embodiments”, “one or more embodiments”, “someembodiments”, and “one embodiment” mean “one or more (but not all)embodiments of the present invention(s)” unless expressly specifiedotherwise.

The terms “including”, “comprising”, “having” and variations thereofmean “including but not limited to”, unless expressly specifiedotherwise.

The enumerated listing of items does not imply that any or all of theitems are mutually exclusive, unless expressly specified otherwise.

The terms “a”, “an” and “the” mean “one or more”, unless expresslyspecified otherwise.

Devices that are in communication with each other need not be incontinuous communication with each other, unless expressly specifiedotherwise. In addition, devices that are in communication with eachother may communicate directly or indirectly through one or moreintermediaries.

A description of an embodiment with several components in communicationwith each other does not imply that all such components are required. Onthe contrary a variety of optional components are described toillustrate the wide variety of possible embodiments of the presentinvention.

Further, although process steps, method steps, algorithms or the likemay be described in a sequential order, such processes, methods andalgorithms may be configured to work in alternate orders. In otherwords, any sequence or order of steps that may be described does notnecessarily indicate a requirement that the steps be performed in thatorder. The steps of processes described herein may be performed in anyorder practical. Further, some steps may be performed simultaneously.

When a single device or article is described herein, it will be readilyapparent that more than one device/article (whether or not theycooperate) may be used in place of a single device/article. Similarly,where more than one device or article is described herein (whether ornot they cooperate), it will be readily apparent that a singledevice/article may be used in place of the more than one device orarticle or a different number of devices/articles may be used instead ofthe shown number of devices or programs. The functionality and/or thefeatures of a device may be alternatively embodied by one or more otherdevices which are not explicitly described as having suchfunctionality/features. Thus, other embodiments of the present inventionneed not include the device itself.

At least certain operations that may have been illustrated in thefigures show certain events occurring in a certain order. In alternativeembodiments, certain operations may be performed in a different order,modified or removed. Moreover, steps may be added to the above describedlogic and still conform to the described embodiments. Further,operations described herein may occur sequentially or certain operationsmay be processed in parallel. Yet further, operations may be performedby a single processing unit or by distributed processing units.

The foregoing description of various embodiments of the invention hasbeen presented for the purposes of illustration and description. It isnot intended to be exhaustive or to limit the invention to the preciseform disclosed. Many modifications and variations are possible in lightof the above teaching. It is intended that the scope of the invention belimited not by this detailed description, but rather by the claimsappended hereto. The above specification, examples and data provide acomplete description of the manufacture and use of the composition ofthe invention. Since many embodiments of the invention can be madewithout departing from the spirit and scope of the invention, theinvention resides in the claims hereinafter appended.

What is claimed is:
 1. A method, comprising: maintaining a plurality offunctions to configure a unit of a storage volume, wherein each of theplurality of functions, in response to being applied to the unit of thestorage volume, configures the unit of the storage volume differently;computing, via a processor, statistics on growth rate of data and accesscharacteristics of the data stored in the unit of the storage volume;and determining which of the plurality of functions to apply to the unitof the storage volume, based on the computed statistics, wherein theplurality of functions includes full allocation, thin provisioning, datacompression, and data deduplication in a decreasing order of performancein terms of performing operations on the unit of the storage volume, andin an increasing order of efficiency in terms of storage requirements inthe unit of the storage volume, wherein: a new unit is initiallyprovisioned as fully allocated and does not use thin provisioning, datacompression or data deduplication; and based on the computed statistics,migrating the new unit to use thin provisioning, data compression, ordata deduplication.
 2. The method of claim 1, wherein the computedstatistics include determining how much duplicative data is present onthe unit the storage volume, the method further comprising: applyingdata deduplication to the unit of the storage volume, in response todetermining that duplicative data present on the unit of the storagevolume exceeds a predetermined threshold and access time requirement forthe unit of the storage volume is greater than a predetermined accesstime rate.
 3. The method of claim 1, the method further comprising:applying full allocation to the unit of the storage volume, in responseto determining that access time requirement for the unit of the storagevolume is less than a predetermined threshold amount of time.
 4. Themethod of claim 1, wherein the computed statistics include determininghow much the data stored on the unit of the storage volume is capable ofbeing compressed, the method further comprising: compressing the datastored on the unit of the storage volume, in response to determiningthat access time requirement for the data will be met subsequent to thecompressing of the data stored in the unit of the storage volume.
 5. Themethod of claim 1, wherein: a first unit that is a most frequentlyaccessed unit of the storage volume is maintained as a fully allocatedunit; a second unit that is a less frequently accessed unit of thestorage volume compared to the first unit is maintained as a thinprovisioned unit; a third unit that is a still less frequently accessedunit of the storage volume compared to the second unit is maintained asa compressed unit; and a fourth unit that is a least frequently accessedunit of the storage volume is maintained as a deduplicated unit.
 6. Themethod of claim 1, wherein if compression throughput rates are able tosatisfy access patterns on the new unit, migrating the new unit that isinitially provisioned as fully allocated to a compressed unit.
 7. Asystem, comprising: a memory; and a processor coupled to the memory,wherein the processor performs operations, the operations comprising:maintaining a plurality of functions to configure a unit of a storagevolume, wherein each of the plurality of functions, in response to beingapplied to the unit of the storage volume, configures the unit of thestorage volume differently; computing statistics on growth rate of dataand access characteristics of the data stored in the unit of the storagevolume; and determining which of the plurality of functions to apply tothe unit of the storage volume, based on the computed statistics,wherein the plurality of functions includes full allocation, thinprovisioning, data compression, and data deduplication in a decreasingorder of performance in terms of performing operations on the unit ofthe storage volume, and in an increasing order of efficiency in terms ofstorage requirements in the unit of the storage volume, wherein: a newunit is initially provisioned as fully allocated and does not use thinprovisioning, data compression or data deduplication; and based on thecomputed statistics, migrating the new unit to use thin provisioning,data compression, or data deduplication.
 8. The system of claim 7,wherein the computed statistics include determining how much duplicativedata is present on the unit the storage volume, the operations furthercomprising: applying data deduplication to the unit of the storagevolume, in response to determining that duplicative data present on theunit of the storage volume exceeds a predetermined threshold and accesstime requirement for the unit of the storage volume is greater than apredetermined access time rate.
 9. The system of claim 7, the operationsfurther comprising: applying full allocation to the unit of the storagevolume, in response to determining that access time requirement for theunit of the storage volume is less than a predetermined threshold amountof time.
 10. The system of claim 7, wherein the computed statisticsinclude determining how much the data stored on the unit of the storagevolume is capable of being compressed, the operations furthercomprising: compressing the data stored on the unit of the storagevolume, in response to determining that access time requirement for thedata will be met subsequent to the compressing of the data stored in theunit of the storage volume.
 11. The system of claim 7, wherein: a firstunit that is a most frequently accessed unit of the storage volume ismaintained as a fully allocated unit; a second unit that is a lessfrequently accessed unit of the storage volume compared to the firstunit is maintained as a thin provisioned unit; a third unit that is astill less frequently accessed unit of the storage volume compared tothe second unit is maintained as a compressed unit; and a fourth unitthat is a least frequently accessed unit of the storage volume ismaintained as a deduplicated unit.
 12. The system of claim 7, wherein ifcompression throughput rates are able to satisfy access patterns on thenew unit, migrating the new unit that is initially provisioned as fullyallocated to a compressed unit.
 13. A storage device, wherein codestored in the storage device when executed via a processor causesoperations, the operations comprising: maintaining a plurality offunctions to configure a unit of a storage volume, wherein each of theplurality of functions, in response to being applied to the unit of thestorage volume, configures the unit of the storage volume differently;computing statistics on growth rate of data and access characteristicsof the data stored in the unit of the storage volume; and determiningwhich of the plurality of functions to apply to the unit of the storagevolume, based on the computed statistics, wherein the plurality offunctions includes full allocation, thin provisioning, data compression,and data deduplication in a decreasing order of performance in terms ofperforming operations on the unit of the storage volume, and in anincreasing order of efficiency in terms of storage requirements in theunit of the storage volume, wherein: a new unit is initially provisionedas fully allocated and does not use thin provisioning, data compressionor data deduplication; and based on the computed statistics, migratingthe new unit to use thin provisioning, data compression, or datadeduplication.
 14. The storage device of claim 13, wherein the computedstatistics include determining how much duplicative data is present onthe unit the storage volume, the operations further comprising: applyingdata deduplication to the unit of the storage volume, in response todetermining that duplicative data present on the unit of the storagevolume exceeds a predetermined threshold and access time requirement forthe unit of the storage volume is greater than a predetermined accesstime rate.
 15. The storage device of claim 13, the operations furthercomprising: applying full allocation to the unit of the storage volume,in response to determining that access time requirement for the unit ofthe storage volume is less than a predetermined threshold amount oftime.
 16. The storage device of claim 13, wherein the computedstatistics include determining how much the data stored on the unit ofthe storage volume is capable of being compressed, the operationsfurther comprising: compressing the data stored on the unit of thestorage volume, in response to determining that access time requirementfor the data will be met subsequent to the compressing of the datastored in the unit of the storage volume.
 17. The storage device ofclaim 13, wherein: a first unit that is a most frequently accessed unitof the storage volume is maintained as a fully allocated unit; a secondunit that is a less frequently accessed unit of the storage volumecompared to the first unit is maintained as a thin provisioned unit; athird unit that is a still less frequently accessed unit of the storagevolume compared to the second unit is maintained as a compressed unit;and a fourth unit that is a least frequently accessed unit of thestorage volume is maintained as a deduplicated unit.
 18. The storagedevice of claim 13, wherein if compression throughput rates are able tosatisfy access patterns on the new unit, migrating the new unit that isinitially provisioned as fully allocated to a compressed unit.